### Ler Heroes

Podemos **ler** `Hero`s do banco de dados usando um `select()`. Podemos incluir um `limit` e `offset` para paginar os resultados.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[48:55] hl[51:52,54] *}

### Ler um Único Hero

Podemos **ler** um único `Hero`.

                                                        TF_Buffer* buf,
                                                        TF_Status* status);

// Some TF ops need a step container to be set to limit the lifetime of some
// resources (mostly TensorArray and Stack, used in while loop gradients in
// graph mode). Calling this on a context tells it to start a step.
TF_CAPI_EXPORT extern void TFE_ContextStartStep(TFE_Context* ctx);

    get() = gradleProperty(BUILD_VERSION_QUALIFIER)


val Project.defaultPerformanceBaselines: Provider<String>
    get() = gradleProperty(DEFAULT_PERFORMANCE_BASELINES)


// null means no limit: use all available executors
val Project.maxTestDistributionRemoteExecutors: Int?
    get() = gradleProperty(MAX_TEST_DISTRIBUTION_REMOTE_EXECUTORS).orNull?.toInt()

val Project.maxTestDistributionLocalExecutors: Int?

  @Throws(IOException::class)
  override fun onStream(stream: Http2Stream) {
    stream.close(ErrorCode.REFUSED_STREAM, null)
  }

  /** When settings are received, adjust the allocation limit. */
  override fun onSettings(
    connection: Http2Connection,
    settings: Settings,
  ) {
    lock.withLock {
      val oldLimit = allocationLimit
      allocationLimit = settings.getMaxConcurrentStreams()

   *
   * <p>Note that the cache <b>may evict an entry before this limit is exceeded</b>. For example, in
   * the current implementation, when {@code concurrencyLevel} is greater than {@code 1}, each
   * resulting segment inside the cache <i>independently</i> limits its own size to approximately
   * {@code maximumSize / concurrencyLevel}.
   *

    assertEquals("[yam, bam, jam, ham]", Iterables.toString(list));
  }

  public void testLimit() {
    Iterable<String> iterable = newArrayList("foo", "bar", "baz");
    Iterable<String> limited = Iterables.limit(iterable, 2);

    List<String> expected = ImmutableList.of("foo", "bar");
    List<String> actual = newArrayList(limited);
    assertEquals(expected, actual);
    assertCanIterateAgain(limited);

     */
    int findMin(int index, int len) {
      if (index >= size) {
        return -1;
      }
      checkState(index > 0);
      int limit = min(index, size - len) + len;
      int minIndex = index;
      for (int i = index + 1; i < limit; i++) {
        if (compareElements(i, minIndex) < 0) {
          minIndex = i;
        }
      }
      return minIndex;
    }

// maximum number of in flight async nodes. Enqueuing of additional async ops
// after the limit is reached blocks until some inflight nodes finishes.
// The effect is bounding the memory held by inflight TensorHandles that are
// referenced by the inflight nodes.
// A recommended value has not been established.
// A value of 0 removes the limit, which is the behavior of TensorFlow 2.11.
// When is_async is false, the value is ignored.

	if len(p) <= 1 {
		// Nothing to do.
		return
	}
	var ok bool
	for _, z := range p {
		if z.Available > 0 && z.MaxUsedPct < max {
			ok = true
			break
		}
	}
	if !ok {
		// All above limit.
		// Do not modify
		return
	}

	// Remove entries that are above.
	for i, z := range p {
		if z.Available > 0 && z.MaxUsedPct < max {
			continue
		}
		p[i].Available = 0
	}
}

    * This will be used by the **automatic docs**.
    * It will also be used by automatic client code generation tools.

But most importantly:

* It will **limit and filter** the output data to what is defined in the return type.
    * This is particularly important for **security**, we'll see more of that below.

## `response_model` Parameter